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CONSENSUS: a Shiny application of dementia evaluation and reporting for the KU ADC longitudinal Clinical Cohort database

BACKGROUND: The University of Kansas Alzheimer’s Disease Center (KU ADC) maintains several large databases to track participant recruitment, enrollment, and capture various research-related activities. It is challenging to manage and coordinate all the research-related activities. One of the crucial...

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Autores principales: Sharma, Palash, Montgomery, Robert N, Graves, Rasinio S, Meyer, Kayla, Hunt, Suzanne L, Vidoni, Eric D, Mahnken, Jonathan D, Swerdlow, Russell H, Burns, Jeffrey M, Mudaranthakam, Dinesh Pal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8327371/
https://www.ncbi.nlm.nih.gov/pubmed/34350395
http://dx.doi.org/10.1093/jamiaopen/ooab060
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author Sharma, Palash
Montgomery, Robert N
Graves, Rasinio S
Meyer, Kayla
Hunt, Suzanne L
Vidoni, Eric D
Mahnken, Jonathan D
Swerdlow, Russell H
Burns, Jeffrey M
Mudaranthakam, Dinesh Pal
author_facet Sharma, Palash
Montgomery, Robert N
Graves, Rasinio S
Meyer, Kayla
Hunt, Suzanne L
Vidoni, Eric D
Mahnken, Jonathan D
Swerdlow, Russell H
Burns, Jeffrey M
Mudaranthakam, Dinesh Pal
author_sort Sharma, Palash
collection PubMed
description BACKGROUND: The University of Kansas Alzheimer’s Disease Center (KU ADC) maintains several large databases to track participant recruitment, enrollment, and capture various research-related activities. It is challenging to manage and coordinate all the research-related activities. One of the crucial activities involves generating a consensus diagnosis and communicating with participants and their primary care providers. PROCESS: To effectively manage the cohort, the KU ADC utilizes a combination of open-source electronic data capture (EDC) (i.e. REDCap), along with other homegrown data management and analytic systems developed using R-studio and Shiny. PROCESS EVALUATION: In this article, we describe the method and utility of the user-friendly dashboard that was developed for the rapid reporting of dementia evaluations which allows clinical researchers to summarize recruitment metrics, automatically generate letters to both participants and healthcare providers, which ultimately help optimize workflows. CONCLUSIONS: We believe this general framework would be beneficial to any institution that build reports and summarizing key metrics of their research from longitudinal databases.
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spelling pubmed-83273712021-08-03 CONSENSUS: a Shiny application of dementia evaluation and reporting for the KU ADC longitudinal Clinical Cohort database Sharma, Palash Montgomery, Robert N Graves, Rasinio S Meyer, Kayla Hunt, Suzanne L Vidoni, Eric D Mahnken, Jonathan D Swerdlow, Russell H Burns, Jeffrey M Mudaranthakam, Dinesh Pal JAMIA Open Case Report BACKGROUND: The University of Kansas Alzheimer’s Disease Center (KU ADC) maintains several large databases to track participant recruitment, enrollment, and capture various research-related activities. It is challenging to manage and coordinate all the research-related activities. One of the crucial activities involves generating a consensus diagnosis and communicating with participants and their primary care providers. PROCESS: To effectively manage the cohort, the KU ADC utilizes a combination of open-source electronic data capture (EDC) (i.e. REDCap), along with other homegrown data management and analytic systems developed using R-studio and Shiny. PROCESS EVALUATION: In this article, we describe the method and utility of the user-friendly dashboard that was developed for the rapid reporting of dementia evaluations which allows clinical researchers to summarize recruitment metrics, automatically generate letters to both participants and healthcare providers, which ultimately help optimize workflows. CONCLUSIONS: We believe this general framework would be beneficial to any institution that build reports and summarizing key metrics of their research from longitudinal databases. Oxford University Press 2021-08-02 /pmc/articles/PMC8327371/ /pubmed/34350395 http://dx.doi.org/10.1093/jamiaopen/ooab060 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Case Report
Sharma, Palash
Montgomery, Robert N
Graves, Rasinio S
Meyer, Kayla
Hunt, Suzanne L
Vidoni, Eric D
Mahnken, Jonathan D
Swerdlow, Russell H
Burns, Jeffrey M
Mudaranthakam, Dinesh Pal
CONSENSUS: a Shiny application of dementia evaluation and reporting for the KU ADC longitudinal Clinical Cohort database
title CONSENSUS: a Shiny application of dementia evaluation and reporting for the KU ADC longitudinal Clinical Cohort database
title_full CONSENSUS: a Shiny application of dementia evaluation and reporting for the KU ADC longitudinal Clinical Cohort database
title_fullStr CONSENSUS: a Shiny application of dementia evaluation and reporting for the KU ADC longitudinal Clinical Cohort database
title_full_unstemmed CONSENSUS: a Shiny application of dementia evaluation and reporting for the KU ADC longitudinal Clinical Cohort database
title_short CONSENSUS: a Shiny application of dementia evaluation and reporting for the KU ADC longitudinal Clinical Cohort database
title_sort consensus: a shiny application of dementia evaluation and reporting for the ku adc longitudinal clinical cohort database
topic Case Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8327371/
https://www.ncbi.nlm.nih.gov/pubmed/34350395
http://dx.doi.org/10.1093/jamiaopen/ooab060
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